This section is intended to provide a background or context to the invention that is recited in the claims. The description herein may include concepts that could be pursued, but are not necessarily ones that have been previously conceived or pursued. Therefore, unless otherwise indicated herein, what is described in this section is not prior art to the description and claims in this application and is not admitted to be prior art by inclusion in this section.
Vision systems may use one or more imaging units such as cameras to collect image data of an agricultural field or similar geographical area. The image data may be utilized to facilitate the identification of multiple crop rows in the agricultural field. Information resulting from the identification of the multiple crop rows can then be used to aid in guiding a vehicle through or about the multiple crop rows.
To be useful for practical applications, such as the guidance of a vehicle with reference to the identified multiple crop rows, a data processor is generally required to have adequate throughput or processing capacity to provide a sufficiently rapid or real-time assessment of the collected image data. For example, the techniques generally require extensive pre-processing algorithms such as binarization processes and threshold calculations in order to accurately identify crop rows from images taken of an agricultural field scene. In addition, the principal pattern recognition methods used with conventional crop row detection techniques are highly sensitive to noise picked up in the field scene images.
Accordingly, a technique is desirable for efficiently determining the position of crop rows in a field by reducing or minimizing the processing burden on the data processor, as well as compensating for image aberrations is desirable.